Related papers: ConfPred: A layered intergrowth structure predicti…
The intercalation of metals beneath graphene offers a powerful route to stabilizing and protecting novel two-dimensional (2D) phases. The epitaxial growth of Pb monolayers on SiC(0001), combined with the relatively large spacing of the…
We report the controlled growth of single crystals of intercalated layered Lu$ _{1+n} $Fe$ _{2+n} $O$ _{4+3n-\delta} $ ($ n $=1,2) with different oxygen stoichiometries ${\delta}$. For the first time crystals sufficiently stoichiometric to…
We report on the synthesis of large single crystals of a new FeSe-layer superconductor Cs0.8(FeSe0.98)2. X-ray powder diffraction, neutron powder-diffraction and magnetization measurements have been used to compare the crystal structure and…
The layered iron superconductors are discussed using electronic structure calculations. The four families of compounds discovered so far, including Fe(Se,Te) have closely related electronic structures. The Fermi surface consists of…
The recent discovery of superconductivity under high pressure in the two-leg ladder compound BaFe$_2$S$_3$ [H. Takahashi et al., Nature Materials 14, 1008 (2015)] opens a broad avenue of research, because it represents the first report of…
We report on the theoretical discovery of Iron monocarbide binary sheets stabilized at two-dimensional confined space, which we call tetragonal-FeC (t-FeC) and orthorhombic-FeC (o-FeC), respectively. From the energy viewpoint, the proposed…
The discovery of high-temperature superconductivity in Fe-based compounds [1,2] has triggered numerous investigations on the interplay between superconductivity and magnetism [3] and, more recently, on the enhancement of transition…
Two iron-chalcogenide superconductors Li(x)[C5H5N](y)Fe(2-z)Se2 and Cs(x)Fe(2-z)Se2 in the as-prepared and annealed state have been investigated by means of the Moessbauer spectroscopy versus temperature. Multi-component spectra are…
An image-based deep learning framework is developed in this paper to predict damage and failure in microstructure-dependent composite materials. The work is motivated by the complexity and computational cost of high-fidelity simulations of…
New candidate ground states at 1:4, 1:2, and 1:1 compositions are identified in the well-known Fe-B system via a combination of ab initio high-throughput and evolutionary searches. We show that the proposed oP12-FeB2 stabilizes by a break…
We propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on a metallic surfaces under electrochemical conditions. Stage one uses ab initio simulations to provide…
The recently developed evolutionary algorithm USPEX proved to be a tool that enables accurate and reliable prediction of structures for a given chemical composition. Here we extend this method to predict the crystal structure of polymers by…
We have synthesized two iron fluo-arsenides $A$Ca$_2$Fe$_4$As$_4$F$_2$ with $A$ = Rb and Cs, analogous to the newly discovered superconductor KCa$_2$Fe$_4$As$_4$F$_2$. The quinary inorganic compounds crystallize in a body-centered…
The iron-based superconductors that contain FeAs layers as the fundamental building block in the crystal structures have been rationalized in the past using ideas based on the Fermi Surface nesting of hole and electron pockets when in the…
The interplay between superconductivity, magnetism and crystal structure in iron-based superconductors is a topic of great interest amongst the condensed matter physics community as it is thought to be the key to understanding the…
A subtle balance between competing interactions in strongly correlated systems can be easily tipped by additional interfacial interactions in a heterostructure. This often induces exotic phases with unprecedented properties, as recently…
Despite an artificial intelligence-assisted modeling of disordered crystals is a widely used and well-tried method of new materials design, the issues of its robustness, reliability, and stability are still not resolved and even not…
Ultrafast diffraction imaging is a powerful tool to retrieve the geometric structure of gas-phase molecules with combined picometre spatial and attosecond temporal resolution. However, structural retrieval becomes progressively difficult…
Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…
Fluids under nanoscale confinement differ -- and often dramatically -- from their bulk counterparts. A notorious feature of nanoconfined fluids is their inhomogeneous density profile along the confining dimension, which plays a key role in…